Triple
T11738110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | António Lobo Antunes |
E279082
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | As Naus |
E277190
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: As Naus | Statement: [António Lobo Antunes, notableWork, As Naus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: As Naus Context triple: [António Lobo Antunes, notableWork, As Naus]
-
A.
As Naus
chosen
As Naus is a novel by Portuguese writer António Lobo Antunes that explores the psychological and social aftermath of Portugal’s colonial wars and decolonization.
-
B.
Jako
Jako is a German sportswear and equipment company known for producing football kits and athletic apparel for professional and amateur teams.
-
C.
Nauvo
Nauvo is a Finnish island village and former municipality in the Turku Archipelago, known for its maritime heritage, summer tourism, and scenic coastal landscapes.
-
D.
Nass
Nass is a surname most notably associated with the fictional character Annabeth Nass from the television series "Hart of Dixie."
-
E.
Nom
Nom is a domain name marketplace and service platform operating under the brand Nom.com.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6aaffec6881908bead509e8621742 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4ef1c4881909ad36dc27b1fe193 |
completed | April 10, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f019c339cc81909967ecfa234e4ab8 |
completed | April 28, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:41 p.m.